详情

原文传递 Development of a behaviorally induced systemoptimal travel demand management system

题名：	Development of a behaviorally induced systemoptimal travel demand management system
其他题名：	1 In the real world,acquiring the latest traffic condition could be challenging but is the perquisite of the routing.When the real-world ATDM system Metropia was built(www.metropia.com),we first relied on the multisource traffic data,including loop sensors,global positioning system(GPS)devices,and cell phones signals,which can cover approximately more than half of the main roads,namely,freeways,highways,and arterial links.Then an"imputation"algorithm was developed to"guess"the traffic condition for the links without any data.Such an"imputation"algorithm was based on network topology and traffic flow characteristics.Lastly,the real user trajectory from our smartphone app Metropia was collected and processed in a real-time fashion,so the app users essentially become the"GPS probe vehicles."
正文语种：	英文
作者：	Xianbiao Hu
关键词：	active traffic and demand management (ATDM);behaviorally induced system optimal;dynamic traffic assignment;system optimal;travel behaviour;travel demand management (TDM)
摘要：	The basic design concept of most advanced traveler information systems (ATIS) is to present generic information to travelers, leaving travelers to react to the information in their own way. This "passive" way of managing traffic by providing generic traffic information makes it difficult to predict the outcome and may even incur an adverse effect, such as overreaction (also referred to as the herding effect). Active traffic and demand management (ATDM) is another approach that has received continual attention from both academic research and real-world practice, aiming to effectively influence people's travel demand, provide more travel options, coordinate between travelers, and reduce the need for travel. The research discussed in this article deals with how to provide users with a travel option that aims to minimize the marginal system impact that results from this routing. The goal of this research is to take better advantage of the available real-time traffic information provided by ATIS, to further improve the system level traffic condition from User Equilibrium (UE), or a real-world traffic system that is worse than UE, toward System Optimal (SO), and avoid passively managing traffic. A behaviorally induced, systemoptimal travel demand management model is presented to achieve this goal through incremental routing. Both analytical derivation and numerical analysis have been conducted on Tucson network in Arizona, as well as on the Capital Area Metropolitan Planning Organization (CAMPO) network in Austin, TX. The outcomes of both studies show that our proposed modeling framework is promising for improving network traffic conditions toward SO, and results in substantial economic savings.
出版年：	2017
论文唯一标识：	J-96Y2017V21N01002
英文栏目名称：	Articles
期刊名称：	Journal of Intelligent Transportation Systems Technology Planning and Operations
拼音刊名(出版物代码)：	J-96
卷：	21
期：	01
页码：	12-25